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Estimating the Q-value through ensemble uncertainty not only relaxes the policy constraint strength but also enhances the out-of-distribution generalization ...
To address the above concerns, offline reinforcement learning with generative adversarial networks and uncertainty estimation (GANUE) is proposed. This ...
Apr 14, 2024 · Article on Offline Reinforcement Learning with Generative Adversarial Networks and Uncertainty Estimation, published in on 2024-04-14 by Lan ...
This paper addresses a problem of set-valued state estimation for uncertain continuous-time systems via limited capacity communication channels.
Apr 11, 2024 · 2: OFFLINE REINFORCEMENT LEARNING WITH GENERATIVE ADVERSARIAL NETWORKS AND UNCERTAINTY ESTIMATION. Lan Wu, Quan Liu, Lihua Zhang, Zhigang ...
Abstract. To facilitate offline reinforcement learning, uncertainty esti- mation is commonly used to detect out-of-distribution data.
Oct 5, 2021 · From this intuition, we propose an uncertainty-based model-free offline RL method that effectively quantifies the uncertainty of the Q-value ...
This repository provides a survey on the applications of deep generative models for offline reinforcement learning and imitation learning.
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Jun 13, 2024 · Offline reinforcement learning (RL) can learn optimal policies from pre-collected offline datasets without interacting with the environment, but ...
Nov 5, 2024 · In this work, we propose Q-Distribution guided Q-learning (QDQ) which pessimistic Q-value on OOD regions based on uncertainty estimation.